Alec Coughlin’s Post

I’m not sure which graph I find more interesting, the Bain & Company or the Accenture one, but they’re both intriguing. The amount of AI capital being invested and associated Enterprise activity is incredible but adoption takes time…more time than most of us would like but that’s just the way it is. Infrastructure → Platforms → Applications. Big fan of Benedict Evans' writing including "The AI Summer 07.09" edition of his newsletter. “It does take time to change your habits and ways of thinking around an entirely new kind of tool (remember when we printed out emails?). We can be certain that the models will get better at least to some extent - agents, voice and multimodal will expand the problems they can solve. But I’ve also argued (here last October, for example) that an LLM by itself is not a product - it’s a technology that can enable a tool or a feature, and it needs to be unbundled or rebundled into new framings, UX and tools to be become useful. That takes even more time.” “I think you can see all of the same issues in this data from Bain, surveying enterprise use of LLMs. Again, this is a glass half-empty / glass half-full chart: there’s a lot of interest, and quite a lot of deployment, but it depends where you look.” “Unlike some surveys, which just ask, in effect, ‘is anyone at all anywhere in your organisation using this?’ (um, yes), Bain tried to split the pilots, experiments and trials from the deployment. Everyone has a bunch of tests, but far fewer people are trusting something in their business to this yet, and all of that varies a huge amount depending on your use cases. LLMs are already very useful for coding and marketing, but much less useful for lawyers or HR (though of course lawyers are notably slow adopters of any new tech).” “Accenture, meanwhile, gave us a great illustration of the scale of that enterprise experimentation, but also how much it’s only experimentation for now - again, a glass half-full / half-empty illustration. Last summer it proudly announced that it had already done $300m of ‘generative AI’ work for clients… and that it had done 300 projects. Even an LLM can divide 300 by 300 - that’s a lot of pilots, not deployment. The number has gone up a lot since then, but what’s the mix? Indeed, with Boston Consulting Group (BCG) saying that it expects 20% of its revenue this year will be helping big companies work out what to do about generative AI, the single biggest business from this in 2024 might be for consultants explaining what it is. (It’s the only thing that anyone wants to talk to me about.)” Link below to the newsletter.